GET
/
api
/
{projectId}
/
training
/
keras
/
{learnId}
/
metadata
Keras metadata
curl --request GET \
  --url https://studio.edgeimpulse.com/v1/api/{projectId}/training/keras/{learnId}/metadata \
  --header 'x-api-key: <api-key>'
{
  "success": true,
  "error": "<string>",
  "created": "2023-11-07T05:31:56Z",
  "layers": [
    {
      "input": {
        "shape": 33,
        "name": "x_input:0",
        "type": "<dtype: 'float32'>"
      },
      "output": {
        "shape": 20,
        "name": "dense_1/Relu:0",
        "type": "<dtype: 'float32'>"
      }
    }
  ],
  "classNames": [
    "<string>"
  ],
  "labels": [
    "<string>"
  ],
  "availableModelTypes": [
    "int8"
  ],
  "recommendedModelType": "int8",
  "modelValidationMetrics": [
    {
      "type": "int8",
      "loss": 123,
      "accuracy": 123,
      "confusionMatrix": [
        [
          31,
          1,
          0
        ],
        [
          2,
          27,
          3
        ],
        [
          1,
          0,
          39
        ]
      ],
      "report": {},
      "onDevicePerformance": [
        {
          "mcu": "<string>",
          "name": "<string>",
          "isDefault": true,
          "latency": 123,
          "tflite": {
            "ramRequired": 123,
            "romRequired": 123,
            "arenaSize": 123,
            "modelSize": 123
          },
          "eon": {
            "ramRequired": 123,
            "romRequired": 123,
            "arenaSize": 123,
            "modelSize": 123
          },
          "eon_ram_optimized": {
            "ramRequired": 123,
            "romRequired": 123,
            "arenaSize": 123,
            "modelSize": 123
          },
          "customMetrics": [
            {
              "name": "<string>",
              "value": "<string>"
            }
          ],
          "hasPerformance": true,
          "profilingError": "<string>"
        }
      ],
      "predictions": [
        {
          "sampleId": 123,
          "startMs": 123,
          "endMs": 123,
          "label": "<string>",
          "prediction": "<string>",
          "predictionCorrect": true,
          "f1Score": 123,
          "anomalyScores": [
            [
              123
            ]
          ]
        }
      ],
      "visualization": "featureExplorer",
      "isSupportedOnMcu": true,
      "mcuSupportError": "<string>",
      "profilingJobId": 123,
      "profilingJobFailed": true,
      "additionalMetrics": [
        {
          "name": "<string>",
          "value": "<string>",
          "fullPrecisionValue": 123,
          "tooltipText": "<string>",
          "link": "<string>"
        }
      ]
    }
  ],
  "hasTrainedModel": true,
  "mode": "classification",
  "objectDetectionLastLayer": "mobilenet-ssd",
  "imageInputScaling": "0..1",
  "thresholds": [
    {
      "key": "min_score",
      "description": "Score threshold",
      "helpText": "Threshold score for bounding boxes. If the score for a bounding box is below this the box will be discarded.",
      "suggestedValue": 123,
      "suggestedValueText": "<string>",
      "value": 0.5
    }
  ],
  "tensorboardGraphs": [
    {
      "title": "<string>",
      "xLabel": "<string>",
      "yLabel": "<string>",
      "description": "<string>",
      "hideInUI": true,
      "data": [
        {
          "title": "<string>",
          "values": [
            123
          ]
        }
      ]
    }
  ]
}

Authorizations

x-api-key
string
header
required

Path Parameters

projectId
integer
required

Project ID

learnId
integer
required

Learn Block ID, use the impulse functions to retrieve the ID

Query Parameters

excludeLabels
boolean

If set to "true", the "labels" field is left empty (which can be big on e.g. regression projects).

Response

200 - application/json

OK

The response is of type object.